Monday, June 30, 2008

Correlation and causality reached the U.S. Supreme Court last week -- or at least the written dissent of one justice -- as a 5-4 majority interpreted the U.S. Constitution's Second Amendment to confer an individual or personal right to gun ownership, as opposed to only a collective right (i.e., belonging to "a well-regulated militia...").

Cases such as this are supposed to be decided on constitutional issues, in terms of the history and meaning of the document. However, as sometimes happens, policy issues such as whether gun-control laws are good or bad for society find their way into the discourse.

Shown below is a passage from a New York Timesarticle, which quotes Justice Stephen Breyer's attempt to make sense of empirical studies of gun and crime (Breyer's full dissenting opinion is available here).

According to the study, published last year in The Harvard Journal of Law and Public Policy, European nations with more guns had lower murder rates. As summarized in a brief filed by several criminologists and other scholars supporting the challenge to the Washington law, the seven nations with the most guns per capita had 1.2 murders annually for every 100,000 people. The rate in the nine nations with the fewest guns was 4.4.Justice Breyer was skeptical about what these comparisons proved. “Which is the cause and which the effect?” he asked. “The proposition that strict gun laws cause crime is harder to accept than the proposition that strict gun laws in part grow out of the fact that a nation already has a higher crime rate.”

Whatever positions individuals might take on gun-control legislation, I hope most would agree that careful examination of the direction of causality from inherently correlational studies -- like that exhibited by Breyer -- is a good thing.

8-9 September: 2 days of tutorials on causality, probability and their use in science.10-12 September: CAPITS 2008 a 3-day conference on causality and probability in the sciences.15-19 September: a week of advanced research seminars on causality and probability.